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With the rise of cryptocurrencies, many new applications built on decentralized blockchains have emerged. Blockchains are full-stack distributed systems where multiple sub-systems interact. While many deployed blockchains and decentralized…
Federated learning has been rapidly evolving and gaining popularity in recent years due to its privacy-preserving features, among other advantages. Nevertheless, the exchange of model updates and gradients in this architecture provides new…
Data marketplaces (DMs) promote the benefits of the Internet of Things (IoT) in smart cities. To facilitate the easy exchanges of real-time IoT data streams between device owners and third-party applications, it is required to provide…
Multiparty computation (MPC) consists in several parties engaging in joint computation in such a way that each party's input and output remain private to that party. Whereas MPC protocols for specific computations have existed since the…
Cloud computing enables clients with limited computational power to economically outsource their large scale computations to a public cloud with huge computational power. Cloud has the massive storage, computational power and software which…
Security and privacy in Direct Load Control (DLC) is a fundamental challenge in smart grids. In this paper, we propose a blockchain-based framework to increase security and privacy of DLC. We propose a method whereby participating nodes…
A decentralized online petition system enables individuals or groups to create, sign, and share petitions without a central authority. Using blockchain technology, these systems ensure the integrity and transparency of the petition process…
Many of the problems that arise in the context of blockchains and decentralized finance can be seen as variations on classical problems of distributed computing. The smart contract model proposed here is intended to capture both the…
Linear Regression (LR) is a classical machine learning algorithm which has many applications in the cyber physical social systems (CPSS) to shape and simplify the way we live, work and communicate. This paper focuses on the data analysis…
To address the large amount of energy wasted by blockchains, we propose a decentralized consensus protocol for blockchains in which the computation can be used to search for good approximate solutions to any optimization problem. Our…
Private blockchain networks are used by enterprises to manage decentralized processes without trusted mediators and without exposing their assets publicly on an open network like Ethereum. Yet external parties that cannot join such networks…
The emergence of cloud computing provides a new computing paradigm for users -- massive and complex computing tasks can be outsourced to cloud servers. However, the privacy issues also follow. Fully homomorphic encryption shows great…
In order to solve security and privacy issues of centralized cloud services, the edge computing network is introduced, where computing and storage resources are distributed to the edge of the network. However, native edge computing is…
Federated learning is a decentralized machine learning paradigm that allows multiple clients to collaborate by leveraging local computational power and the models transmission. This method reduces the costs and privacy concerns associated…
Blockchain technology ensures secure and trustworthy data flow between multiple participants on the chain, but interoperability of on-chain and off-chain data has always been a difficult problem that needs to be solved. To solve the problem…
Decentralized optimization enables multiple devices to learn a global machine learning model while each individual device only has access to its local dataset. By avoiding the need for training data to leave individual users' devices, it…
Secure multi-party computation (MPC) is a broad cryptographic concept that can be adopted for privacy-preserving computation. With MPC, a number of parties can collaboratively compute a function, without revealing the actual input or output…
Edge computing is a distributed computing paradigm that relies on computational resources of end devices in a network to bring benefits such as low bandwidth utilization, responsiveness, scalability and privacy preservation. Applications…
Machine learning has recently enabled large advances in artificial intelligence, but these tend to be highly centralized. The large datasets required are generally proprietary; predictions are often sold on a per-query basis; and published…
Blockchain has made an impact on today's technology by revolutionizing the financial industry in its utilization on cryptocurrency and the features it provided on decentralization. With the current trend of pursuing the decentralized…